Research on deep learning decoding method for polar codes in ACO-OFDM spatial optical communication system

Kangrui Liu , Ming Li , Sizhe Chen , Jiashun Qu , Ming’ou Zhou

Optoelectronics Letters ›› 2025, Vol. 21 ›› Issue (7) : 427 -433.

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Optoelectronics Letters ›› 2025, Vol. 21 ›› Issue (7) : 427 -433. DOI: 10.1007/s11801-025-4094-9
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Research on deep learning decoding method for polar codes in ACO-OFDM spatial optical communication system

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Abstract

Aiming at the problem that the bit error rate (BER) of asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) space optical communication system is significantly affected by different turbulence intensities, the deep learning technique is proposed to the polarization code decoding in ACO-OFDM space optical communication system. Moreover, this system realizes the polarization code decoding and signal demodulation without frequency conduction with superior performance and robustness compared with the performance of traditional decoder. Simulations under different turbulence intensities as well as different mapping orders show that the convolutional neural network (CNN) decoder trained under weak-medium-strong turbulence atmospheric channels achieves a performance improvement of about 102 compared to the conventional decoder at 4-quadrature amplitude modulation (4QAM), and the BERs for both 16QAM and 64QAM are in between those of the conventional decoder.

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Kangrui Liu, Ming Li, Sizhe Chen, Jiashun Qu, Ming’ou Zhou. Research on deep learning decoding method for polar codes in ACO-OFDM spatial optical communication system. Optoelectronics Letters, 2025, 21(7): 427-433 DOI:10.1007/s11801-025-4094-9

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References

[1]

MohsanS A, KhanM A, AmjadH. Hybrid FSO/RF networks: a review of practical constraints, applications and challenges[J]. Optical switching and networking, 2023, 47: 100697

[2]

AlnajjarS H, AliM H, AbassA K. Enhancing performance of hybrid FSO/fiber optic communication link utilizing multi-channel configuration[J]. Journal of optical communications, 2022, 43(1): 165-170

[3]

YamadaH, SuganumaH, MaeharaF. System capacity analysis of asynchronous FBMC and OFDM systems in the presence of adjacent channel interference and multipath fading[C]. 2022 IEEE Radio and Wireless Symposium (RWS), January 16–19, 2022, Las Vegas, NV, USA, 2022 New York IEEE 171-173

[4]

BaiR, HranilovicS, WangZ. Low-complexity layered ACO-OFDM for power-efficient visible light communications[J]. IEEE transactions on green communications and networking, 2022, 6(3): 1780-1792

[5]

TahaB, FayedH A, AlyM H, et al.. A reduced PAPR hybrid OFDM visible light communication system[J]. Optical and quantum electronics, 2022, 54(12): 815

[6]

NiwareebaR, CoxM A, ChengL. Low complexity hybrid SLM for PAPR mitigation for ACO OFDM[J]. ICT express, 2022, 8(1): 72-76

[7]

BrakensiekJ, GopiS, MakamV. Generic Reed-Solomon codes achieve list-decoding capacity[C]. Proceedings of the 55th Annual ACM Symposium on Theory of Computing, January 20–23, 2023, 2023 New York ACM 1488-1501

[8]

BeelenP, PuchingerS, RosenkildeJ. Twisted Reed-Solomon codes[J]. IEEE transactions on information theory, 2022, 68(5): 3047-3061

[9]

ConR, ShpilkaA, TamoI. Reed Solomon codes against adversarial insertions and deletions[J]. IEEE transactions on information theory, 2023, 69(5): 2991-3000

[10]

YU L, LIN S J, HOU H, et al. Reed-Solomon coding algorithms based on Reed-Muller transform for any number of parities[J]. IEEE transactions on computers, 2023.

[11]

TuL T, NguyenT N, DuyT T, et al.. Broadcasting in cognitive radio networks: a fountain codes approach[J]. IEEE transactions on vehicular technology, 2022, 71(10): 11289-11294

[12]

NguyenN L, TuL T, NguyenT N, et al.. Performance on cognitive broadcasting networks employing fountain codes and maximal ratio transmission[J]. Radio engineering, 2023, 32(1): 1-10

[13]

HE X, CAI K. Basis-finding algorithm for decoding fountain codes for DNA-based data storage[J]. IEEE transactions on information theory, 2023.

[14]

BocharovaI E, KudryashovB D, Ovsyan-NikovE P, et al.. Design and analysis of NB QC-LDPC codes over small alphabets[J]. IEEE transactions on communications, 2022, 70(5): 2964-2976

[15]

HylaJ, SułekW, IzydorczykW, et al.. Efficient LDPC encoder design for IOT-type devices[J]. Applied sciences, 2022, 12(5): 2558

[16]

MohanN, GhassemlooyZ, LiE, et al.. The BER performance of a FSO system with polar codes under weak turbulence[J]. IET optoelectronics, 2022, 16(2): 72-80

[17]

SelviM, JeevaS, JaswanthJ. Review of performance of LDPC codes for various OFDM systems[C]. 2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), January 18–19, 2024, Lalitpur, Nepal, 2024 New York IEEE 864-869

[18]

YoussefA A. Bootstrapped low complex iterative LDPC decoding algorithms for free-space optical communication links[J]. EURASIP journal on wireless communications and networking, 2023, 2023(1): 78

[19]

KongS. Analysis of the encoding and decoding process of polar code[J]. Highlights in science, engineering and technology, 2023, 53: 144-152

[20]

ArikanE. Channel polarization: a method for constructing capacity-achieving codes for symmetric binary-input memoryless channels[J]. IEEE transactions on information theory, 2009, 55(7): 3051-3073

[21]

ArikanE. A performance comparison of polar codes and Reed-Muller codes[J]. IEEE communications letters, 2008, 12(6): 447-449

[22]

XuY, ZhaoL, YangN, et al.. Propagation characteristics of partially coherent twisted Laguerre-Gaussian beam in atmospheric turbulence with anisotropy[J]. Journal of modern optics, 2022, 69(4): 200-209

[23]

HeshamH, IsmailT. Hybrid NOMA-based ACO-FBMC/OQAM for next-generation indoor optical wireless communications using LiFi technology[J]. Optical and quantum electronics, 2022, 54(3): 201

[24]

CondoC, BioglioV, HafermannH, et al.. Practical product code construction of polar codes[J]. IEEE transactions on signal processing, 2020, 68: 2004-2014

[25]

MohsanS A H, KhanM A, AmjadH. Hybrid FSO/RF networks: a review of practical constraints, applications and challenges[J]. Optical switching and networking, 2023, 47: 100697

[26]

SafiH, SharifiA A, DabiriM T, et al.. Adaptive channel coding and power control for practical FSO communication systems under channel estimation error[J]. IEEE transactions on vehicular technology, 2019, 68(8): 7566-7577

[27]

TangC Research on polar code decoding algorithm based on deep neural network[D], 2020 Xi’an Xi’an Electronic Science and Technology University (in Chinese)

[28]

FrancoisC Deep learning with Python[M], 2021 2nd edition

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